AWS Machine Learning

For a supervised machine learning (ML) problem, labels are values expected to be learned and predicted by a model. To obtain accurate labels, ML practitioners can either record them in real time or conduct offline […]

Have you noticed that your shopping preferences are influenced by the weather? For example, on hot days would you rather drink a lemonade vs. a hot coffee?
Customers from consumer-packaged goods (CPG) and retail […]

You might use traditional methods to forecast future business outcomes, but these traditional methods are often not flexible enough to account for varying factors, such as weather or promotions, outside of the […]

Feature engineering is a process of applying transformations on raw data that a machine learning (ML) model can use. As an organization scales, this process is typically repeated by multiple teams that use the […]

Amazon Personalize now enables you to tap into the information trapped in product descriptions, product reviews, movie synopses, or other unstructured text and use it when generating personalized recommendations. […]

If you need to integrate image analysis into your business process to detect objects or scenes unique to your business domain, you need to build your own custom machine learning (ML) model. Building a custom model […]

In Part 1 of this series, we walk through a continuous model improvement machine learning (ML) workflow with Amazon Rekognition Custom Labels and Amazon Augmented AI (Amazon A2I). We explained how we use AWS Step […]

Healthcare technology companies often turn to AWS to help them accelerate their clinical and business objectives. MEDHOST has provided enterprise information technology and electronic health record (EHR) solutions […]

AWS just announced the General Availability of Amazon HealthLake, a HIPAA-eligible service for healthcare providers, health insurance companies, and pharmaceutical companies to securely store, transform, query, […]

Amazon HealthLake is a new, HIPAA-eligible service designed to store, transform, query, and analyze health data at scale. You can bring your healthcare data into Amazon HealthLake using Fast Healthcare […]

Amazon HealthLake is a new HIPAA-eligible service designed to store, transform, query, and analyze health data at scale. Amazon HealthLake removes the heavy lifting of organizing, indexing, and structuring patient […]

For many enterprises, critical business information is often stored as unstructured data scattered across multiple content repositories. It is challenging for organizations to make this information available to […]

Anomaly detection is the process of identifying items, events, or occurrences that have different characteristics from the majority of the data. It has many applications in various fields, like fraud detection for […]

Defect detection during manufacturing processes is a vital step to ensure product quality. The timely detection of faults or defects and taking appropriate actions are essential to reduce operational and […]

This post outlines the best practices for provisioning Amazon SageMaker Studio for data science teams and provides reference architectures and AWS CloudFormation templates to help you get started. We use AWS […]

Last year, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML).
JumpStart hosts 196 […]

In this post, we show you how to use Amazon Rekognition and AWS DeepLens to detect, and analyze occupancy in a retail business to optimize workforce utilization. Retailers often need to make decisions to improve […]

Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. […]

In this post, you learn how to create a MLOps project to automate the deployment of an Amazon SageMaker endpoint with multiple production variants for A/B testing. You also deploy a general purpose API and testing […]

Hugging Face is the technology startup, with an active open-source community, that drove the worldwide adoption of transformer-based models thanks to its eponymous Transformers library. Earlier this year, Hugging […]